Purpose of the role:

As a Data Scientist, the person will be responsible for bringing a combination of mathematical rigor and innovative algorithm design to create recipes that extract relevant insights from billions of rows of data to meaningfully improve user experience.

KEY RESPONSIBILITIES:

• Collect, clean, and preprocess structured and unstructured data from various sources.
• Develop and implement machine learning models and statistical algorithms.
• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Collaborate with cross-functional teams to understand business requirements and translate them into data solutions.
• Visualize data insights using tools like Tableau, Power BI, or matplotlib/seaborn.
• Communicate findings clearly to stakeholders through reports and presentations.
• Continuously improve data processes and model performance.

Experience:

• Graduate degree or Phd in the following areas: Statistics, Data Science, Computer Science or relevant science or engineering discipline.
• Machine learning, data science skills with strong programming background in python.
• 5+ years of experience with common data science toolkits, such as scikit-learn, R, etc. Excellence in at least one of these is highly desirable.
• Great communication skills.
• Good Analytical skills
• Data-oriented personality

Skills & Competencies:

Must Have:

• Python
• scikit-learn, TensorFlow, or PyTorch.
• Spark, Hadoop, Kafka,
• AWS/ Azure/ Google Cloud

Good to Have

• Spark (AWS EMR, Databricks), AWS Lambda
• Spark Streaming and Batch
• Avro, Parquet
• Stream Data Platforms: AWS Kinesis
• MySQL, Cassandra, HBase, MongoDB, RDBMS
• Caching Frameworks(ElasticCache/Redis)
• Elasticsearch, Beats, Logstash, Kibana
• Java, Scala, Go, R
• Git, Maven, Gradle, Jenkins
• Rancher, Puppet, Concourse, Docker, Ansible, Kubernetes
• Linux
• Presto, Athena
• Keras, Pandas)
• Visualization suite (AWS Quicksight, Grafana)